Enterprise resource planning (ERP) systems and related data management systems are of great importance for companies of all kinds of industries and technological disciplines. A significant financial and time investment is spent on the prohibition and cure of erroneous data within ERP systems, as erroneous data may result in erroneous manufacturing processes, data loss, and may render crucially important data sets useless.
Some ERP systems already come with some integrated modules for ensuring data quality. Often, external systems are used alternatively or in addition to the integrated modules in order to guarantee and maintain data quality. A concern connected with using external systems for data quality check is that additional time is required for adapting the external system to the semantic structure of the business objects of the ERP system or even to the data structures used for storing the business objects in order to enable the external system to execute the quality checks. Thus, the execution, as well as the setup of data quality checks in the context of an ERP system may be time consuming.
A further concern is that data quality checks, and in particular, global data quality checks involving the processing of a plurality of business objects from one or more distributed data sources may be highly time consuming. Thus, an ongoing data quality check may constitute a bottleneck for the performance of an ERP system. A further concern is that the runtime behavior of the quality checks may vary greatly and unpredictably in dependence on the evaluated data and/or the response time of external resources comprising some parts of the ERP system's data to be evaluated.